Carnegie Mellon University
15721 Database System Design and Implementation
Spring 2003 - C. Faloutsos
Final exam study guide



Several of the papers of the `Red book' are available through the ACM digital library, free of charge to CMU.

Material to be examined

The Roots

  1. E.F. Codd, A Relational Model of Data for Large Shared Data Banks, ACM SIGMOD, CACM, 13(6), 1970
  2. Astrahan, M. , et al., System R: Relational Approach to Database Management, ACM TODS, 1(2), 1976
  3. Chamberlin, D., et al., A History and Evaluation of System R, Communications of the ACM, 24(10), 1981
  4. Stonebraker, M., et al., (1976) The Design and Implementation of INGRES, ACM TODS, 1(3), 1976
  5. Stonebraker, M., (1980) Retrospection on a Database System, ACM TODS, 5(2), 1980
Relational Implementation Techniques
  1. Stonebraker, M., Operating System Support for Database Management, Communications of the ACM, 24(7), 1981
  2. A. Guttman, R-Trees: A Dynamic Index Structure for Spatial Searching, Proceedings of the ACM SIGMOD Conference, 1984
  3. J.M Hellerstein, et al, Generalized Search Trees for Database Systems, VLDB 1995.
  4. (extra) J. Orenstein: Spatial Query Processing in an Object Oriented Database System, SIGMOD 1986.
  5. Chou, H., and DeWitt, D., An Evaluation of Buffer Management Strategies for Relational Database Systems, Proceedings of the 11th VLDB Conference, 1985
  6. (extra) O'Neil, E. , O'Neil, P., and Weikum, G., The LRU-K Replacement Algorithm for Database Disk Buffering, Proceedings of the ACM SIGMOD Conference, Washington, D.C., June 1993
  7. (extra) T. Johnson and D. Shasha, 2Q: A Low Overhead High Performance Buffer Management Replacement Algorithm.VLDB 1994
  8. Shapiro, L., Join Processing in Database Systems with Large Main Memories, ACM TODS, 11(3), September 1986
  9. Selinger, P., et al., Access Path Selection in a Relational Database Management System, Proceedings of the ACM SIGMOD Conference, Boston, MA, 1979


Concurrency Control
  1.  Gray, J., et al., "Granularity of Locks and Degrees of Consistency in a Shared Database", IFIP Working Conference on Modelling of Database management Systems, AFIPS Press, 1976
  2. H. T. Kung and John T. Robinson, On Optimistic Methods for Concurrency Control, VLDB ACM TODS 6(2), June 1981, pp.213-226
  3. Philip L. Lehman, S. Bing Yao, Efficient Locking for Concurrent Operations on B-Trees, ACM TODS 6(4): 650-670, 1981
  4. T. Haerder & A. Reuter: "Principles of Transaction-Oriented Database  Recovery." Computing Surveys 15(4): 287-317 (1983)
  5. (extra) Michael Franklin, Concurrency Control and Recovery, The Computer Science and Engineering Handbook (1997)
Distributed Database Systems
  1. Williams, et al., "R*: An Overview of the Architecture." IBM Research Report RJ3325.
  2. L. Mackert & G. Lohman, "R* Optimizer Validation and Performance Evaluation for Distributed Queries", VLDB 1986.
  3. Mohan, Lindsay, and Obermark, Transaction Management in the R* Distributed Database Management System, TODS 11(4), 1986
Parallel Database Systems
  1. D. J. DeWitt and J. Gray, Parallel Database Systems: The Future of High Performance Database Processing, Communications of the ACM, June 1992
  2. D. J. DeWitt, S. Ghandeharizadeh, D. Schneider, H. Hsiao, A. Bricker, and R. Rasmussen, The GAMMA Database Machine Project, IEEE Transactions on Knowledge and Data Engineering, Vol. 2, No. 1, March 1990
  1. Anon, et al: "A Measure of Transaction Processing Power." Datamation,  31(7): 112-118
Data Mining
  1. J. Gray, S. Chaudhuri, A. Bosworth, A. Layman, D. Reichart, M. Venkatrao, F. Pellow, and H. Pirakesh, Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals, Data Mining and Knowledge Discovery 1, 29 , 1997
  2. R. Agrawal, T. Imielinski, and A. Swami. Mining assosiation rules between sets of items in large databases. SIGMOD 93, pages 207--216, May 1993.
  3. Agrawal, R. and R. Srikant, Fast Algorithms for Mining Association Rules, Proceedings of the VLDB Conference, 1994

The introductions, in ALL chapters of the 'red book'  (Chapters 1-9, included)

Extra: SVD and Ratio Rules

  1. Flip Korn, H.V. Jagadish and Christos Faloutsos “Efficiently Supporting Ad Hoc Queries in Large Datasets of Time Sequences”, ACM SIGMOD, Tucson, AZ, pp. 289-300, May 1997.
  2. Korn, F., A. Labrinidis, et al. (1998). Ratio Rules: A New Paradigm for Fast, Quantifiable Data Mining. VLDB, New York, NY. (mainly, the interpretation of the rules and the eigenvectors)
  3. Appendix D in 'multimedia' book
Extra: Fractals
From the papers below, we need mainly the definitions of fractal dimensions, and the description of box-counting.
  1. Christos Faloutsos and Ibrahim Kamel, Beyond Uniformity and Independence: Analysis of R-trees Using  the Concept of Fractal Dimension, PODS, Minneapolis, MN,  May 24-26, 1994, pp. 4-13
  2. Alberto Belussi and Christos Faloutsos Estimating the Selectivity of Spatial Queries Using the `Correlation' Fractal Dimension VLDB, Sept. 1995, Zurich, Switzerland, pp. 299-310
Extra: Sensor  and Stream data mining; indexing, wavelets, and forecasting
  1. From 'multimedia' book:
  2. Byoung-Kee Yi et al.: Online Data Mining for Co-Evolving Time Sequences, ICDE 2000. (mainly, the idea behind multivariate linear regression and 'recursive least squares')
  3. Mengzhi Wang, et al.: Data Mining Meets Performance Evaluation: Fast Algorithms for Modeling Bursty Traffic, ICDE 2002, San Jose, CA. (mainly, the idea behind the 80-20 rule and multifractals)

Last modified: 4/30/2003 by C. Faloutsos